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Recently there has been increased interest in fitting generative graph models to real-world networks. In particular, Bl\"asius et al. have proposed a framework for systematic evaluation of the expressivity of random graph models. We extend…

Social and Information Networks · Computer Science 2024-05-14 Benjamin Dayan , Marc Kaufmann , Ulysse Schaller

In a recent paper, Girard proposes to use his recent construction of a geometry of interaction in the hyperfinite factor in an innovative way to characterize complexity classes. We begin by giving a detailed explanation of both the choices…

Logic in Computer Science · Computer Science 2015-01-23 Clément Aubert , Thomas Seiller

Geometric modeling by constraints, whose applications are of interest to communities from various fields such as mechanical engineering, computer aided design, symbolic computation or molecular chemistry, is now integrated into standard…

Computational Geometry · Computer Science 2018-03-06 Samy Ait-Aoudia , Adel Moussaoui , Khaled Abid , Dominique Michelucci

Graphs are common mathematical structures that are visual and intuitive. They constitute a natural and seamless way for system modelling in science, engineering and beyond, including computer science, biology, business process modelling,…

Formal Languages and Automata Theory · Computer Science 2020-12-03 Berthold Hoffmann , Mark Minas

In many ways, graphs are the main modality of data we receive from nature. This is due to the fact that most of the patterns we see, both in natural and artificial systems, are elegantly representable using the language of graph structures.…

Machine Learning · Computer Science 2023-09-06 Petar Veličković

Many real-world phenomena are naturally modeled by graphs and networks. However, classical graph models are often limited to pairwise interactions and may not adequately capture the richer structures that arise in practice. Higher-order…

Social and Information Networks · Computer Science 2026-05-18 Takaaki Fujita , Florentin Smarandache

Building upon [1], this study aims to introduce fractal geometry into graph theory, and to establish a potential theoretical foundation for complex networks. Specifically, we employ the method of substitution to create and explore…

Dynamical Systems · Mathematics 2024-05-29 Nero Ziyu Li

The space complexity of functional programs is not well understood. In particular, traditional implementation techniques are tailored to time efficiency, and space efficiency induces time inefficiencies, as it prefers re-computing to…

Logic in Computer Science · Computer Science 2021-04-30 Beniamino Accattoli , Ugo Dal Lago , Gabriele Vanoni

Graph embeddings learn the structure of networks and represent it in low-dimensional vector spaces. Community structure is one of the features that are recognized and reproduced by embeddings. We show that an iterative procedure, in which a…

Physics and Society · Physics 2024-07-30 Bianka Kovács , Sadamori Kojaku , Gergely Palla , Santo Fortunato

Geometric graphs are a special kind of graph with geometric features, which are vital to model many scientific problems. Unlike generic graphs, geometric graphs often exhibit physical symmetries of translations, rotations, and reflections,…

Artificial intelligence (AI) has undergone a renaissance recently, making major progress in key domains such as vision, language, control, and decision-making. This has been due, in part, to cheap data and cheap compute resources, which…

Historically, there have been many attempts to produce an appropriate mathematical formalism for modeling the nature of physical space, such as Euclid's geometry, Descartes' system of Cartesian coordinates, the Argand plane, Hamilton's…

History and Philosophy of Physics · Physics 2016-02-23 James M. Chappell , Azhar Iqbal , Derek Abbott

We study the implications of the modeling choice to use a graph, instead of a hypergraph, to represent real-world interconnected systems whose constituent relationships are of higher order by nature. Such a modeling choice typically…

Machine Learning · Computer Science 2024-01-17 Yanbang Wang , Jon Kleinberg

Graphs are fundamental data structures which concisely capture the relational structure in many important real-world domains, such as knowledge graphs, physical and social interactions, language, and chemistry. Here we introduce a powerful…

Machine Learning · Computer Science 2018-03-12 Yujia Li , Oriol Vinyals , Chris Dyer , Razvan Pascanu , Peter Battaglia

Signed graphs are an emergent way of representing data in a variety of contexts where antagonistic interactions exist. These include data from biological, ecological, and social systems. Here we propose the concept of communicability for…

Metric Geometry · Mathematics 2025-03-20 Fernando Diaz-Diaz , Ernesto Estrada

The aim of these notes is to provide a reasonably short and "hands-on" introduction to the differential calculus on associative algebras over a field of characteristic zero. Following a suggestion of Ginzburg's we call the resulting theory…

Mathematical Physics · Physics 2017-06-28 Alberto Tacchella

The concept of viewing graph solvability has gained significant interest in the context of structure-from-motion. A viewing graph is a mathematical structure where nodes are associated to cameras and edges represent the epipolar geometry…

Computer Vision and Pattern Recognition · Computer Science 2025-04-07 Federica Arrigoni , Kathlén Kohn , Andrea Fusiello , Tomas Pajdla

In this paper we consider aspects of geometric observability for hypergraphs, extending our earlier work from the uniform to the nonuniform case. Hypergraphs, a generalization of graphs, allow hyperedges to connect multiple nodes and…

Dynamical Systems · Mathematics 2024-04-12 Joshua Pickard , Cooper Stansbury , Amit Surana , Indika Rajapakse , Anthony Bloch

We construct and study a class of algebras associated to generalized layered graphs, i.e. directed graphs with a ranking function on their vertices. Each finite directed acyclic graph admits countably many structures of a generalized…

Combinatorics · Mathematics 2008-06-11 Vladimir Retakh , Robert Lee Wilson

Many complex systems are composed of interacting parts, and the underlying laws are usually simple and universal. While graph neural networks provide a useful relational inductive bias for modeling such systems, generalization to new system…

Machine Learning · Computer Science 2022-11-21 Zhe Li , Andreas S. Tolias , Xaq Pitkow